Programmable SC neural networks for solving nonlinear programming problems

Neural networks for the online solution of linear and nonlinear programming problems are presented. Adopting switched-capacitor (SC) techniques, the proposed circuits have the advantages of VLSI implementation and programmability. Simulation results show the stability and availability of the discret...

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Bibliographic Details
Published in1990 IEEE International Symposium on Circuits and Systems (ISCAS) pp. 2837 - 2840 vol.4
Main Authors Jou, I.-C., Wu, C.-Y., Liu, R.-Y.
Format Conference Proceeding
LanguageEnglish
Published IEEE 1990
Subjects
Circuit simulation
Computer architecture
Linear programming
Neural networks
Quadratic programming
Resistors
Switched capacitor circuits
Switching circuits
Symmetric matrices
Very large scale integration
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Summary:Neural networks for the online solution of linear and nonlinear programming problems are presented. Adopting switched-capacitor (SC) techniques, the proposed circuits have the advantages of VLSI implementation and programmability. Simulation results show the stability and availability of the discrete-time neural network. The optimum solutions are obtained in near real time.< >
DOI:10.1109/ISCAS.1990.112601